Method and apparatus for pain management with sleep detection

ABSTRACT

An Example of a system for providing a patient with pain management may include a sleep monitoring circuit, a pain relief device, and a control circuit. The sleep monitoring circuit may be configured to sense one or more sleep signals from the patient and to determine a sleep state of the patient using the one or more sleep signals. The one or more sleep signals may include one or more physiological signals corresponding to the sleep state of the patient. The pain relief device may be configured to deliver one or more pain relief therapies. The control circuit may be configured to control the delivery of the one or more pain relief therapies using therapy parameters and to adjust the therapy parameters based on the determined sleep state.

CLAIM OF PRIORITY

This application claims the benefit of priority under 35 U.S.C. § 119(e)of U.S. Provisional Patent Application Ser. No. 62/457,456, filed onFeb. 10, 2017, which is herein incorporated by reference in itsentirety.

TECHNICAL FIELD

This document relates generally to medical devices and more particularlyto a pain management system that determines sleep state and control painmanagement based on the sleep state.

BACKGROUND

Pain may result from an injury, a disease (e.g., arthritis,fibromyalgia), or even a medical treatment (e.g., certain cancertreatment). Various treatments are applied for pain management, such asmedication, psychotherapy, electrical stimulation, thermal therapy, andtheir various combinations. Examples of electrical stimulation for painmanagement include Transcutaneous Electrical Nerve Stimulation (TENS)delivered by a TENS unit and Spinal Cord Stimulation (SCS) that may bedelivered by an implantable neuromodulation systems. Pain treatment maybe prescribed based on an assessment of a patient's symptoms andunderlying conditioning and titrated based on the patient's response tothe treatment. As pain is not directly measurable by a machine, theassessment of the condition and the titration of the therapy may dependon questioning the patient. Because pain is affected by various factors,such as physical, physiological, and mental states of the patient, thatvary with time, dependency on patient feedback limits timely adjustmentor optimization of a pain suppression therapy.

SUMMARY

An Example (e.g., “Example 1”) of a system for providing a patient withpain management may include a sleep monitoring circuit, a pain reliefdevice, and a control circuit. The sleep monitoring circuit may beconfigured to sense one or more sleep signals from the patient and todetermine a sleep state of the patient using the one or more sleepsignals. The one or more sleep signals may include one or morephysiological signals corresponding to the sleep state of the patient.The pain relief device may be configured to deliver one or more painrelief therapies. The control circuit may be configured to control thedelivery of the one or more pain relief therapies using therapyparameters and to adjust the therapy parameters based on the determinedsleep state.

In Example 2, the subject matter of Example 1 may optionally beconfigured to include an implantable medical device that includes atleast portions of the sleep monitoring circuit, the pain relief device,and the control circuit.

In Example 3, the subject matter of any one or any combination ofExamples 1 and 2 may optionally be configured such that the pain reliefdevice includes a neurostimulator configured to deliverneurostimulation, and the control circuit is configured to control thedelivery of the neurostimulation using stimulation parameters and adjustthe stimulation parameters based on the determined sleep state.

In Example 4, the subject matter of any one or any combination ofExamples 1 to 3 may optionally be configured such that the sleepmonitoring circuit includes one or more sleep sensors configured tosense the one or more sleep signals from the patient, a sleep signalsensing circuit configured to process the one or more sleep signals, asleep parameter generator circuit configured to generate one or moresleep parameters corresponding to the sleep state of the patient usingthe processed one or more sleep signals, and a sleep analyzer circuit todetermine the sleep state of the patient using the generated one or moresleep parameters and a predetermined relationship between values of theone or more sleep parameters and the sleep state of the patient.

In Example 5, the subject matter of Example 4 may optionally beconfigured such that the one or more sleep sensors include one or moreimplantable sensors.

In Example 6, the subject matter of any one or any combination ofExamples 4 and 5 may optionally be configured such that the one or moresleep sensors include one or more externally wearable sensors.

In Example 7, the subject matter of any one or any combination ofExamples 4 to 6 may optionally be configured such that the sleepanalyzer circuit includes a sleep parameter analyzer circuit configuredto receive and analyze the generated one or more sleep parameters and asleep score generator circuit configured to compute a sleep score usingan outcome of the analysis of the generated one or more sleepparameters. The sleep score is indicative of the sleep state of thepatient and includes one or more of a number, a sleep signal metric, ora number being a function of the sleep signal metric. The controlcircuit is configured to adjust the therapy parameters using thecomputed sleep score.

In Example 8, the subject matter of any one or any combination ofExamples 4 to 7 may optionally be configured to further include a painmonitoring circuit configured to receive and analyze the sleep state andone or more of a physiological parameter indicative of a physiologicalfunction or physiological state of the patient, a functional parameterindicative of a physical activity or physical state of the patient, or apatient parameter including subjective information provided by thepatient and to compute a pain score using an outcome of the analysis.The pain score indicates a degree of the pain of the patient. Thecontrol circuit is configured to adjust the therapy parameters using thepain score.

In Example 9, the subject matter of any one or any combination ofExamples 4 to 8 may optionally be configured such that the one or moresleep sensors include a three-axis accelerometer configured to sense anaccelerometer signal of the one or more sleep signals.

In Example 10, the subject matter of any one or any combination ofExamples 4 to 9 may optionally be configured such that the one or moresleep sensors include a three-axis gyroscope configured to sense agyroscope signal of the one or more sleep signals.

In Example 11, the subject matter of any one or any combination ofExamples 4 to 10 may optionally be configured such that the one or moresleep sensors include an electrocardiogram (ECG) sensor configured tosense an ECG signal of the one or more sleep signals.

In Example 12, the subject matter of any one or any combination ofExamples 4 to 11 may optionally be configured such that the one or moresleep sensors include an electroencephalogram (EEG) sensor configured tosense an EEG signal of the one or more sleep signals.

In Example 13, the subject matter of any one or any combination ofExamples 4 to 12 may optionally be configured such that the one or moresleep sensors include a temperature sensor configured to sense atemperature signal of the one or more sleep signals.

In Example 14, the subject matter of any one or any combination ofExamples 4 to 13 may optionally be configured such that the one or moresleep sensors include an electrodermal activity (EDA) sensor configuredto sense an EDA signal of the one or more sleep signals.

In Example 15, the subject matter of any one or any combination ofExamples 4 to 14 may optionally be configured such that the one or moresleep sensors include a blood volume pulse (BVP) sensor configured tosense a BVP signal of the one or more sleep signals.

An example (e.g., “Example 16”) of a method for providing a patient withpain management is also provided. The method may include sensing one ormore sleep signals from the patient, determining the sleep state of thepatient using the one or more sleep signals, controlling the delivery ofone or more pain relief therapies using therapy parameters, adjustingthe therapy parameters based on the determined sleep state, anddelivering the one or more pain relief therapies. The one or more sleepsignals may include one or more physiological signals corresponding to asleep state of the patient.

In Example 17, the subject matter of determining the sleep state asfound in Example 16 may optionally further include determining a sleepstage.

In Example 18, the subject matter of delivering the one or more painrelief therapies as found in Example 17 may optionally further includedelivering neurostimulation, and the subject matter of adjusting thetherapy parameters based on the determined sleep state as found inExample 17 may optionally further include adjusting stimulationparameters based on the determined sleep stage.

In Example 19, the subject matter of determining the sleep stage asfound in any one or any combination of Examples 17 and 18 may optionallyfurther include producing a sleep score using the one or more sleepsignals, and the subject matter of adjusting the therapy parametersbased on the determined sleep state as found in any one or anycombination of Examples 17 and 18 may optionally further includeadjusting the therapy parameters based on the produced sleep score. Thesleep score is indicative of the sleep stage and includes one or more ofa number, a sleep signal metric, or a number being a function of thesleep signal metric.

In Example 20, the subject matter of any one or any combination ofExamples 16 to 19 may optionally further include receiving and analyzingthe determined sleep state and one or more of a physiological parameterindicative of a physiological function or physiological state of thepatient, a functional parameter indicative of a physical activity orphysical state of the patient, or a patient parameter includingsubjective information provided by the patient and to compute a painscore using an outcome of the analysis, the pain score indicating adegree of the pain of the patient, and the subject matter of adjustingthe therapy parameters based on the determined sleep state as found inany one or any combination of Examples 16 to 19 may optionally includeadjusting the therapy parameters based on the pain score.

In Example 21, the subject matter of sensing the one or more sleepsignals from the patient as found in any one or any combination ofExamples 16 to 20 may optionally further include sensing one or more ofan accelerometer signal, a gyroscope signal, an electrocardiogram (ECG)signal, an electroencephalogram (EEG) signal, a temperature signal ofthe one or more sleep signals, an electrodermal activity (EDA) signal, ablood volume pulse (BVP) signal, or a bioelectric impedance signal.

In Example 22, the subject matter of delivering one or more pain relieftherapies as found in any one or any combination of Examples 16 to 21may optionally further include delivering the one or more pain relieftherapies from a medical device implanted in the patient or externallyworn by the patient.

In Example 23, the subject matter of sensing the one or more sleepsignals as found in any one or any combination of Examples 16 to 22 mayoptionally further include sensing at least one sleep signal of the oneor more sleep signals using a sensor implanted in the patient.

In Example 24, the subject matter of sensing the one or more sleepsignals as found in any one or any combination of Examples 16 to 23 mayoptionally further include sensing at least one sleep signal of the oneor more sleep signals using a sensor externally worn by the patient.

In Example 25, the subject matter of sensing the one or more sleepsignals as found in any one or any combination of Examples 22 to 24 mayoptionally further include sensing at least one sleep signal of the oneor more sleep signals using a sensor communicatively coupled to themedical device via a wireless link.

This Summary is an overview of some of the teachings of the presentapplication and not intended to be an exclusive or exhaustive treatmentof the present subject matter. Further details about the present subjectmatter are found in the detailed description and appended claims. Otheraspects of the disclosure will be apparent to persons skilled in the artupon reading and understanding the following detailed description andviewing the drawings that form a part thereof, each of which are not tobe taken in a limiting sense. The scope of the present disclosure isdefined by the appended claims and their legal equivalents.

BRIEF DESCRIPTION OF THE DRAWINGS

The drawings illustrate generally, by way of example, variousembodiments discussed in the present document. The drawings are forillustrative purposes only and may not be to scale.

FIG. 1 illustrates an embodiment of a therapy system.

FIG. 2 illustrates an embodiment of a sleep monitoring circuit, such asmay be used in the therapy system of FIG. 1.

FIG. 3 illustrates another embodiment of a sleep monitoring circuit,such as may be used in the therapy system of FIG. 1.

FIG. 4 illustrates an embodiment of a pain management system.

FIG. 5 illustrates another embodiment of pain management system.

FIG. 6 illustrates an embodiment of a pain monitoring circuit, such asmay be used in the therapy system of FIG. 5.

FIG. 7 illustrates an embodiment of a pain management system, such asone in which the pain management system of FIG. 4 or 5 may beimplemented, and portions of an environment in which the pain managementsystem may be used.

FIG. 8 illustrates an embodiment of a method for pain management.

DETAILED DESCRIPTION

In the following detailed description, reference is made to theaccompanying drawings which form a part hereof, and in which is shown byway of illustration specific embodiments in which the invention may bepracticed. These embodiments are described in sufficient detail toenable those skilled in the art to practice the invention, and it is tobe understood that the embodiments may be combined, or that otherembodiments may be utilized and that structural, logical and electricalchanges may be made without departing from the spirit and scope of thepresent invention. References to “an”, “one”, or “various” embodimentsin this disclosure are not necessarily to the same embodiment, and suchreferences contemplate more than one embodiment. The following detaileddescription provides examples, and the scope of the present invention isdefined by the appended claims and their legal equivalents.

This document discusses, among other things, a system for controllingdelivery of a therapy to a patient based on sleep state of the patient.Conditions, such as chronic pain, can be affected by the patient's sleepstate and quality, and also affects the patient's sleep state andquality. Chronic therapies, such as a therapy for controlling chronicpain, needs optimization of settings during wakefulness that differ fromthose during sleep to maximize its therapeutic benefits to the patient.Sleep quality is an important therapeutic outcome and is associated withthe patient's overall health status. However, it is not often measuredand used in demonstrating therapeutic efficacy. For example, to controldelivery of a pain suppression therapy automatically using a closed-loopsystem, there is a need to use the patient's sleep state as an inputand/or as a measure of efficacy of the therapy.

Physiological conditions during sleep differ greatly from those duringwakefulness, and thus treatment for chronic diseases must reflect thosechanges. For instance, in a chronic pain patient treated with spinalcord stimulation, levels of endogenous neurotransmitters during sleepmay require lesser stimulation current to achieve pain reduction. In analgorithm designed to objectively measure pain, it would be important todistinguish changes in physiological parameters due to sleep changescompared to those due to pain. Because chronic pain patients oftenreport disturbances with their sleep, stages and quality of sleep can beused as a surrogate for pain levels for controlling therapy delivery.Modulating therapy using the patient's sleep state can also save batteryenergy in an implantable device delivering a pain suppression therapybecause less stimulation energy is needed during sleep.

Wakefulness can be differentiated from sleep using a range of differentmodalities, including electroencephalography (EEG), electrodermalactivity (EDA), and heart rate. These modalities can be used todifferentiate various stages of sleep. For example, studies showed thatsleep epochs with EDA peaks are more common during slow-wave sleep thanin rapid eye movement (REM) sleep.

Chronic pain patients are more likely than a healthy person to sufferfrom poor sleep quality and disturbances during sleep. Greater sleepdisturbance was shown to be correlated to greater pain intensity,disability, depression, and physical symptoms. Often it is consideredthat sleep disruption is a consequence of pain. However, this in factcan be a bidirectional relation. Sleep, emotional distress, painperception, daily physical activity appear to link to each other to forma cycle in the patient's daily experience.

In 2015, the National Sleep Foundation conducted a “Sleep in AmericaPoll”, which resulted in a finding that pain was the main factor betweenthe amounts of sleep people said they needed and how much they got(sleep gap), with chronic pain having a larger discrepancy than thosewith acute pain. In addition, pain, stress, and poor health were the keycorrelates of shorter sleep durations and worse sleep quality. However,for those who make sleep a priority, the sleep gap narrows sharply andis associated with less stress and better health.

The present system can include a therapeutic medical device, such as aspinal cord stimulator or intrathecal drug pump, that monitorsphysiological signals from wearable and/or implantable sensors todetermine a patient's stages of sleep and controls delivery of a therapybased on the stage of sleep. In various embodiments, the stage of sleepcan be used as an input signal in an automated closed-loop therapycontrol system and/or as a guide for a user adjusting the therapy. Inthis document, a “user” can include a physician or other care providerwho treats the patient using the present system. While pain managementis discussed as a specific example of application, the present subjectmatter can be applied in controlling and/or optimizing any therapy basedon sleep states. For example, the present subject matter can also beused to control and/or optimize a therapy for improving sleep (e.g., aspinal cord stimulation therapy) that potentially provides a morenatural human sleep pattern, increased rapid eye movement (REM) sleep,etc.

FIG. 1 illustrates an embodiment of a therapy system 100 for deliveringone or more therapies to a patient and controlling the delivery of theone or more therapies based on the patient's sleep state. Therapy system100 can include a sleep monitoring circuit 102, a control circuit 104,and a therapy delivery device 106. Sleep monitoring circuit 102 cansense one or more sleep signals from the patient, and can determine thesleep state of the patient using the one or more sleep signals. The oneor more sleep signals can include one or more physiological signalscorresponding to (or indicative of) the sleep state of the patient. Thesleep state can include a sleep stage and/or one or more indicators ofsleep quality such as time spent at each sleep stage and/or percentageof the time spent at each sleep stage during a sleeping period. Therapydelivery device 106 can deliver the one or more therapies for treatingone or more pathological conditions in which sleep is an importantfactor, and/or in which improved sleep is a desirable outcome. Forexample, the one or more therapies may target at pain suppression and/orsleep quality improvement. Control circuit 104 can control the deliveryof the one or more therapies from therapy delivery device 106 usingtherapy parameters and adjust the therapy parameters based on the sleepstate. In various embodiments, control circuit 106 can optimize thetherapy parameters for the determined sleep state. In variousembodiments, control circuit 104 can execute a closed-loop therapyalgorithm for treating the one or more pathological conditions using thedetermined sleep state as an input.

In various embodiments, circuits of system 100, including its variousembodiments discussed in this document, may be implemented using acombination of hardware and software. For example, sleep monitoringcircuit 102 and control circuit 104, including their various embodimentsdiscussed in this document, may be implemented using anapplication-specific circuit constructed to perform one or moreparticular functions or a general-purpose circuit programmed to performsuch function(s). Such a general-purpose circuit includes, but is notlimited to, a microprocessor or a portion thereof, a microcontroller orportions thereof, and a programmable logic circuit or a portion thereof.

FIG. 2 illustrates an embodiment of a sleep monitoring circuit 202,which represents an example of sleep monitoring circuit 102. Sleepmonitoring circuit 202 can include one or more sleep sensors 210, asleep signal sensing circuit 212, a sleep parameter generator (or sleepparameter generator circuit) 214, and a sleep analyzer (or sleepanalyzer circuit) 216. Sleep sensor(s) 210 can sense the one or moresleep signals from the patient. In various embodiments, sleep sensor(s)210 can include one or more sensors each being incorporated into amedical device such as a medical device that includes control circuit104 and therapy delivery device 106 or being another devicecommunicatively coupled to the medical device via a wired or wirelesscommunication link. In various embodiments, sleep sensor(s) 210 caninclude one or more sensors each being an implantable sensor or anexternally wearable (non-implantable) sensor. The implantable sensor canbe, for example, part of an implantable medical device that can includecontrol circuit 104 and therapy delivery device 106 or being anotherimplantable device communicatively coupled to the implantable medicaldevice via a wired or wireless communication link. The externallywearable sensor can be, for example, part of an externally wearablemedical device that can include control circuit 104 and therapy deliverydevice 106, being another externally wearable device communicativelycoupled to the externally wearable medical device via a wired orwireless communication link, or being an externally wearable devicecommunicatively coupled to an implantable medical device that includescontrol circuit 104 and therapy delivery device 106 via a wired orwireless communication link. Sleep signal sensing circuit 212 canprocess the one or more sleep signals, such as by filtering and/oramplifying each sensed sleep signal. Sleep parameter generator 214 cangenerate one or more sleep parameters corresponding to (or indicativeof) the sleep state of the patient using the processed one or more sleepsignals. For example, sleep parameter generator 214 can detect specifiedfeatures in each sensed sleep signal, measuring amplitude and/or timeassociated with the detected features, and generate one or more sleepparameters using results of the measurement. Sleep analyzer 216 candetermine the sleep state of the patient using the one or more sleepparameters generated by sleep parameter generator 214. Thus, the sleepstate can be indicated by using information extracted from the one ormore sleep signals sensed using one or more sensors 210.

FIG. 3 illustrates another embodiment of a sleep monitoring circuit 302,which represents an example of sleep monitoring circuit 202. Sleepmonitoring circuit 302 can include one or more sleep sensors 310, asleep signal sensing circuit 312, a sleep parameter generator (or sleepparameter generator circuit) 314, and a sleep analyzer (or sleepanalyzer circuit) 316.

Sleep sensor(s) 310 can sense the one or more sleep signals. In theillustrated embodiment, sleep sensor(s) 310 includes an accelerometer310A, a gyroscope 310B, an electrocardiogram (ECG) sensor 310C, anelectroencephalogram (EEG) sensor 310D, a temperature sensor 310E, anelectrodermal activity (EDA) sensor 310F, a blood volume pulse (BVP)sensor 310G, and an impedance sensor 310H. In various embodiments, sleepsensor(s) 310 can include any one or any combination of accelerometer310A, gyroscope 310B, ECG sensor 310C, EEG sensor 310D, temperaturesensor 310E, EDA sensor 310F, BVP sensor 310G, and impedance sensor310H.

Accelerometer 310A can include a three-axis accelerometer to sense anaccelerometer signal. In various embodiment, accelerometer 310A can bean externally wearable device or an implantable device. In thisdocument, a sensor being an externally wearable device include astand-alone externally wearable sensor or a sensor being part of anexternally wearable device that performs another one or more functions;a sensor being an implantable device include a stand-alone implantablesensor or a sensor being part of an implantable device that performsanother one or more functions. An externally wearable device includes adevice configured to be worn on the patient but not to be implanted inthe patient.

Gyroscope 310B can be a three-axis gyroscope to sense a gyroscopesignal. In various embodiments, gyroscope 310B can be an externallywearable device or an implantable device.

ECG sensor 310C can include electrodes for sensing an ECG signal. Invarious embodiments, the ECG signal can include a surface ECG signal, asubcutaneous ECG signal, an epicardial electrogram signal, and/or anendocardial electrogram signal. ECG sensor 310C can be an externallywearable device, part of therapy-delivering device (e.g., a cardiacpacemaker), or an injectable monitoring device.

EEG sensor 310D can include electrodes for sensing an EEG signal. Invarious embodiments, EEG sensor 310D can be an externally wearabledevice (e.g., incorporated into a head cap, one or more ear plugs, or ahead band), a subdermally implantable device, or incorporated into animplantable lead in the brain or on a neural target.

Temperature sensor 310E can sense a temperature signal. In variousembodiments, temperature sensor 310E can be an externally wearabledevice to measure skin temperature, a subdermally implantable device tomeasure peripheral body temperature, or an implantable device to measurecore body temperature.

EDA sensor 310F can sense an EDA signal. In various embodiments, EDAsensor 310F can be a device with surface electrode to measure skinconductance, such as from a hand (palmar surface), a foot (plantarsurface), or a wrist (incorporated into a wrist worn monitoring device)or an implantable device that is communicatively coupled to a conductivelayer (tattoo) on the skin.

BVP sensor 310G can sense a BVP signal. In various embodiments, EDAsensor 310F can be an externally wearable photoplethysmography (PPG)sensor or an implantable device to be positioned adjacent to an arteryand capable of detecting pulsatile information from the artery tocompute the BVP signal. Examples of that artery include common iliacartery, internal iliac artery, gonadal artery, inferior mesentericartery, inferior rectal artery, inferior gluteal artery, superiorgluteal artery, renal artery, and femoral artery. Examples of BVP sensor310G as an implantable device can include a photoplethysmography (PPG)sensor to detect the pulsatile information (including timing, shape, andmorphology) by passing light through the artery, an electricalbioimpedance or impedance cardiography sensor to detect the pulsatileinformation (including timing, shape, and morphology) by measuringchange in impedance across artery as blood flow changes, anaccelerometer to detect the pulsatile information (including timing,shape, and morphology) by measuring changes in position as shape of theartery changes during blood flow, a pressure sensor to be positionedaround the artery to detect the pulsatile information the pulsatileinformation (including timing, shape, and morphology) by directlymeasuring pressure from the artery, and a pressure sensor to bepositioned inside the artery to detect the pulsatile information(including timing, shape, and morphology) by directly measuring pressurewithin the artery. In various embodiments, BVP sensor 310G can includeany one or any combination of these examples.

Impedance sensor 310H can sense a bioelectric impedance. In variousembodiments, impedance sensor 310H can be an externally wearable deviceto measure skin impedance (e.g., allowing for measurement of heart rate)or an implantable device (e.g., allowing for measurement of respirationrate).

Sleep signal sensing circuit 312 can process the one or more sleepsignals sensed by sleep sensor(s) 310, such as by filtering and/oramplifying each sensed sleep signal. Sleep parameter generator 314 cangenerate one or more sleep parameters corresponding to the sleep stateof the patient using the processed one or more sleep signals. Thestructure and functional capability of sleep signal sensing circuit 312and sleep parameter generator 314 depend on which sleep sensor(s) areincluded in sleep sensor(s) 310. In various embodiments, the one or moresleep parameters have one or more values, when used individually or incombination, that can indicate the patient's sleep state.

Sleep analyzer 316 represents an example of sleep analyzer 216 and candetermine the sleep state of the patient using the one or more sleepparameters generated by sleep parameter generator 314. Sleep analyzer316 analyzer 316 can include a sleep parameter analyzer (or sleepparameter analyzer circuit) 318 and a sleep score generator (or sleepscore generator circuit) 320. Sleep parameter analyzer 318 can receiveand analyze the one or more sleep parameters. In one embodiment, the oneor more sleep parameters have values indicative of the patient's sleepstages. For example, the values of the one or more sleep parameters canbe mapped to the sleep stages using data collected from the patient orcollected from a patient population. Sleep stage can be classified as,but not being limited to, awake, slow-wave sleep, REM sleep, non-REM1sleep, or non-REM2. Analysis of the one or more sleep parameters canresult in the current sleep stage of the patient as well as time and/orpercentage of time spent in each sleep stage. Sleep score generator 320can compute a sleep score indicative of sleep stage or quality using anoutcome of the analysis of the one or more sleep parameters. Forexample, value ranges each corresponding to one of sleep stages may bedetermined for each of the one or more sleep parameters for the patient,and used for computing the sleep score as a function of the sleep stage.In various embodiments, the sleep score can include a number (numericalvalue), a sleep signal metric, and/or a number being a function of thesleep signal metric.

In one embodiment, sleep parameter analyzer 318 produces a sleep signalmetric using the one or more sleep parameters. The sleep signal metriccan be a linear or nonlinear combination of multiple sleep parameters.In one embodiment, sleep parameter analyzer 318 produces the sleepsignal metric using the multiple sleep parameters with the weightingfactors each applied to one of these parameters. In one embodiment,sleep parameter analyzer 318 adjusts the weighting factors throughautomatic learning and adaptation to the patient over time (e.g., basedon stored parameters and/or outcomes of analysis, such as featuresextracted from the parameters). In another embodiment, sleep parameteranalyzer 318 allows the weighting factors to be adjusted manually. Inone embodiment, the weighting factors are adjusted according to acalibration schedule or as needed, and the adjustment can be performedby a user such as a physician or other authorized care provider in aclinic, or initiated by the patient and performed by the sleep parameteranalyzer automatically at home. In one embodiment, the weighting factorscan be patient-specific and dynamically changed based on the patient'sconditions and/or activities, such as the pathological condition(s) forwhich the patient is treated, physical condition, time of day, and/orphysical activity. In one embodiment, sleep score generator 320 computesthe sleep score using the sleep signal metric. In one embodiment, painscore generator 320 trends the sleep signal metric and computes thesleep score using the resulting trending of the sleep signal metric.

FIG. 4 illustrates an embodiment of a pain management system 400, whichrepresent an example of therapy system 100. Pain management system 400can include sleep monitoring circuit 102 (including its variousembodiments as discussed for sleep monitoring circuit 202 and 302), acontrol circuit 404, and a pain relief device 406.

Pain relief device 406 can deliver one or more pain relief therapies fortreating chronic pain and/or symptoms associated with the chronic pain.In various embodiments, pain relief device 406 can include aneurostimulator (also referred to as neuromodulator) to deliverneurostimulation (also referred to as neuromodulation) to neural tissuesuch as the spinal cord, brain, and peripheral nerves or a drug pump todelivery drug into the body locally, such as in the intrathecal space.In one embodiment, the neurostimulator includes a pulse generator togenerate and deliver electrical stimulation pulses. In otherembodiments, the neurostimulator can deliver neurostimulation that usesany form of stimulation energy or agent as stimuli that is capable ofmodulating neural activities and/or properties.

In various embodiments, pain relief device 406 can deliver any one orany combination of spinal cord stimulation (SCS), dorsal root ganglia(DRG) stimulation, deep brain stimulation (DBS), motor cortexstimulation (MCS), transcranial direct current stimulation (tDCS),transcutaneous spinal direct current stimulation (tsDCS), trigeminalnerve stimulation, occipital nerve stimulation, vagus nerve stimulation(VNS), sacral nerve stimulation, pudendal nerve stimulation,sphenopalatine ganglion stimulation, sympathetic nerve modulation,multifidus muscle stimulation, adrenal gland modulation, carotidbaroreceptor stimulation, transcutaneous electrical nerve stimulation(TENS), transcranial magnetic stimulation (TMS), tibial nervestimulation, transcranial magnetic stimulation (TMS), radiofrequencyablation (RFA), pulsed radiofrequency ablation, ultrasound therapy,high-intensity focused ultrasound (HIFU), optical stimulation,optogenetic therapy, magnetic stimulation, other peripheral tissuestimulation therapies, other peripheral tissue denervation therapies,drug therapy (such as delivered from a drug pump), and nerve blocks orinjections (such as pharmaceuticals or biologics).

Control circuit 404 can control the delivery of the one or more painrelief therapies using therapy parameters and can adjust the therapyparameters based on the sleep state, such as indicated by the pain scoreor pain signal metric, such that the delivery of the one or more painrelief therapies is adjusted in a way reflecting changes in the sleepstate. When pain relief device 406 delivers the neurostimulation,control circuit 404 can control the delivery of the neurostimulationusing stimulation parameters and can adjust the stimulation parametersbased on the sleep state. In various embodiments, control circuit 404can optimize the stimulation parameters for the determined sleep state.In various embodiments, control circuit 404 can execute a closed-loopneurostimulation algorithm for treating chronic pain or a disorderrelated to the chronic pain using the determined sleep state as aninput.

FIG. 5 illustrates an embodiment of pain management system 500, whichrepresent another example of therapy system 100. Pain management system500 can include sleep monitoring circuit 102 (including its variousembodiments as discussed for sleep monitoring circuit 202 and 302), apain monitoring circuit 530, a control circuit 504, and pain reliefdevice 406.

Pain monitoring circuit 530 can sense one or more pain signals from thepatient and produce a measure of pain of the patient using the one ormore pain-related physiological signals. The one or more pain signalscan include one or more physiological signals corresponding to the painof the patient. In one embodiment, the measure of pain includes a painscore quantitatively indicative of a degree of the pain.

Control circuit 504 can control the delivery of the one or more painrelief therapies from pain relief device 406 using therapy parametersand can adjust the therapy parameters based on the sleep statedetermined by sleep monitoring circuit 102 and the measure of the painproduced by pain monitoring circuit 530. In one embodiment, controlcircuit 504 can adjust the therapy parameters based on the sleep scoreand the pain score. This can be achieved by, for example, producing thepain score using the sleep score as an input, and adjusting the therapyparameters using the pain score. In one embodiment, control circuit 504can control the delivery of the one or more pain relief therapies usingthe therapy parameters and can adjust the therapy parameters using thepain score (which is a function of the sleep score). In one embodiment,control circuit 504 can optimize the stimulation parameters for thedetermined sleep state. In various embodiments, control circuit 504 canexecute a closed-loop therapy algorithm for treating chronic pain or adisorder related to the chronic pain using the pain score (which is afunction of the sleep score) as an input.

FIG. 6 illustrates an embodiment of a pain monitoring circuit 630, whichrepresents an example of pain management circuit 530. In the illustratedembodiment, pain monitoring circuit 630 can determine the measure ofpain, such as the pain score, using the sleep state, such as the sleepscore, as discussed in this document, as well as one or morephysiological parameters each indicative of a physiological function orphysiological state of a patient that is related to pain, one or morefunctional parameters each indicative of a physical activity or physicalstate of the patient that is related to pain, and one or more patientparameters related to the pain, such as a parameter representative ofintensity of the pain specified by the patient. In various embodiments,pain monitoring circuit 630 can determine the pain score using the sleepscore and at least one of a physiological parameter, a functionalparameter, or a patient parameter. In some embodiments, pain monitoringcircuit 630 can determine the pain score using the sleep score and atleast a physiological parameter and a functional parameter.

In the illustrated embodiment, pain monitoring circuit 630 includes oneor more physiological signal sensors 632, a physiological signal sensingcircuit 634, a physiological parameter generator (or physiologicalparameter generator circuit) 636, one or more functional signal sensors638, a functional signal sensing circuit 640, a functional parametergenerator (or functional parameter generator circuit) 642, a patientinformation input device 644, a patient information processing circuit646, a patient parameter generator (or patient parameter generatorcircuit) 648, and a pain analyzer (or pain analyzer circuit) 650. Invarious embodiments, pain monitoring circuit 630 can include at leastone or more physiological signal sensors 632, physiological signalsensing circuit 634, physiological parameter generator 636, one or morefunctional signal sensors 638, functional signal sensing circuit 640,functional parameter generator 642, and pain analyzer 650.

In various embodiments, one or more physiological signal sensors 632 caneach sense one or more physiological signals, and can each be anon-invasive, percutaneous, or implantable sensor. Physiological signalsensing circuit 634 can process the one or more physiological signals.Physiological parameter generator 636 can generate the one or morephysiological parameters using the processed one or more physiologicalsignals. In various embodiments, one or more functional signal sensors638 can sense one or more functional signals, and can each be anon-invasive, percutaneous, or implantable sensor. Functional signalsensing circuit 640 can process the one or more functional signals.Functional parameter generator 642 can generate the one or morefunctional parameters using the processed one or more functionalsignals. In various embodiments, patient information input device 644can receive patient information related to pain. Patient informationprocessing circuit 646 can process the patient information. Patientparameter generator 648 can generate one or more patient parametersusing the processed patient information. Examples of the one or morephysiological parameters, the one or more functional parameters, and theone or more patient parameters are discussed in U.S. Provisional PatentApplication Ser. No. 62/400,336, entitled “METHOD AND APPARATUS FOR PAINMANAGEMENT USING OBJECTIVE PAIN MEASURE”, filed on Sep. 27, 2016,assigned to Boston Scientific Neuromodulation Corporation, which isincorporated herein by reference in its entirety.

Pain analyzer 630 can receive the one or more physiological parametersfrom physiological parameter generator 636, the one or more functionalparameters from functional parameter generator 642, and/or the one ormore patient parameters from patient parameter generator 648, and alsoreceive the sleep score from sleep monitoring circuit 102. Pain analyzer630 can analyze the received parameters including the sleep score andcomputes the pain score using an outcome of the analysis. The pain scoreindicates a degree of the pain. In one embodiment, pain analyzer 650produces a signal metric using the received parameters, and computes thecomposite pain score using the signal metric. In one embodiment, painanalyzer 650 trends the signal metric and computes the composite painscore based on the resulting trending of the signal metric. The signalmetric can be a linear or nonlinear combination of the sleep score andthe one or more physiological parameters, the one or more functionalparameters, and/or the one or more patient parameters. In oneembodiment, pan analyzer 650 produces the signal metric using thereceived parameters with the weighting factors each applied to one ofthese parameters. In various embodiments, pan analyzer 650 adjusts theweighting factors through automatic learning and adaptation to thepatient over time, and/or allows the weighting factors to be adjustedmanually. In one embodiment, the weighting factors can be adjustedaccording to a calibration schedule or as needed, and the adjustment canbe performed by the user. In various embodiments, the weighting factorscan be patient-specific and dynamically changed based on the patient'sconditions and/or activities.

FIG. 7 illustrates an embodiment of a pain management system 700, suchas one in which pain management system 400 or 500 may be implemented,and portions of an environment in which pain management system 700 maybe used. Pain management system 700 can include an implantable medicaldevice 760, an implantable lead or lead system 762 connected toimplantable medical device 760, an external device 780 communicativelycoupled to implantable medical device 760 via a wireless communicationlink 782, a sensor 766 communicatively coupled to implantable medicaldevice 760 via a wireless communication link 768, a sensor 770communicatively coupled to implantable medical device 760 via a wirelesscommunication link 772, and sensor 774 communicatively coupled toimplantable medical device 760 via a wireless communication link 776. Apain monitoring circuit such as pain monitoring circuit 530 or 630 canbe contained within implantable medical device 760 or distributed inimplantable medical device 760 and external device 780. Implantablemedical device 760 can include a therapy device such as pain reliefdevice 406 to deliver one or more pain relief therapies. In variousembodiments, external device 780 can be implemented as a dedicateddevice or in a generic device such as a smartphone, a laptop computer,or a tablet computer.

In the illustrated embodiment, lead or lead system 762 includes anelectrode or electrode array 764. In various embodiments, additional oneor more electrodes can be incorporated onto implantable medical device760. In the illustrated embodiment, sensor 766 can include an EEG sensorsuch as EEG sensor 310D, sensor 770 can include an ECG sensor such asECG sensor 310C, and sensor 774 can include an EDA sensor such as EDAsensor 310F. Sensors 766, 770, and 774 can each be an implantable sensoror an externally wearable sensor. In various embodiments, the sleepscore and the pain score can be produced by implantable medical device760 using signals sensed by sensors 766, 770, and 774.

The sizes and shapes of the elements of pain management system 700 andtheir locations relative to the patient's body are illustrated by way ofexample and not by way of restriction. Pain management system 700 isdiscussed as a specific application of pain management according tovarious embodiments of the present subject matter. In variousembodiments, the present subject matter may be applied in any type ofpain management in controlling delivery of one or more pain reliefenergy and/or agents from an implantable or externally wearable medicaldevice.

FIG. 8 illustrates an embodiment of a method 800 for pain management. Invarious embodiments, pain management system 400, 500, or 700 can beconfigured to perform method 800.

At 802, one or more sleep signals are sensed from the patient. The oneor more sleep signals can include one or more physiological signalscorresponding to the sleep state of the patient. In various embodiments,the one or more sleep signals can each be sensed using a sensorimplanted in the patient or a sensor externally worn by the patient. Invarious embodiments, the one or more sleep signals can each be sensedusing a sensor incorporated into a medical device that delivers a painrelief therapy or a sensor communicatively coupled to the medical devicevia a wireless link. Examples for the one or more sleep signals includean accelerometer signal, a gyroscope signal, an electrocardiogram (ECG)signal, an electroencephalogram (EEG) signal, a temperature signal ofthe one or more sleep signals, an electrodermal activity (EDA) signal,and a blood volume pulse (BVP) signal, as discussed with reference toFIG. 3.

At 804, a sleep state of the patient is determined using the one or moresleep signals. In one embodiment, the sleep state can be awake or asleep stage identified from predefined sleep stages. There are differentways to define sleep stages. In one example, the sleep stages includenon-REM sleep stages 1-4 and REM sleep. In another example, the sleepstages include non-REM sleep stages 1-3 and REM sleep. In yet anotherexample, the sleep stages include slow-wave sleep, REM sleep, non-REM1sleep, or non-REM2. The present subject matter applies regardless of howsleep stages are defined. In various embodiments, a sleep scorerepresenting the sleep state is produced using the one or more sleepsignals. The sleep score can indicate the sleep stage, and can include anumber, a sleep signal metric, or a number being a function of the sleepsignal metric. In various embodiments, in addition to the steep state(e.g., the sleep score), one or more physiological parameters eachindicative of a physiological function or physiological state of thepatient, one or more functional parameters each indicative of a physicalactivity or physical state of the patient, and/or one or more patientparameters each including subjective information provided by the patientare received and analyzed to compute a pain score. The pain score canindicate a degree of the pain of the patient.

At 806, whether the sleep score and/or the pain score indicate a needfor therapy adjustment is determined. If the sleep score and/or the painscore indicate a need for the therapy adjustment, one or more therapyparameters are adjusted using the sleep score and/or the pain score at808, and a pain relief therapy is delivered as controlled using aplurality of therapy parameters including the adjusted one or moretherapy parameters at 810. If the sleep score and/or the pain score donot indicate a need for the therapy adjustment, the pain relief therapyis delivered at 810 without adjusting the one or more therapyparameters. In one embodiment, only the pain score is directly used toindicate the need for therapy adjustment because the pain score isdetermined as a function of the sleep score. Examples of the pain relieftherapy include those deliverable from pain relief device 406, asdiscussed with reference to FIG. 4.

It is to be understood that the above detailed description is intendedto be illustrative, and not restrictive. Other embodiments will beapparent to those of skill in the art upon reading and understanding theabove description. The scope of the invention should, therefore, bedetermined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

What is claimed is:
 1. A method for delivering neurostimulation to apatient, the method comprising: sensing one or more sleep signals andone or more pain signals from the patient, the one or more sleep signalsincluding one or more physiological signals corresponding to sleepstages of the patient, the one or more pain signals indicative of painof the patient; determining the sleep stages of the patient using theone or more sleep signals; determining a measure associated with thepain of the patient using the one or more pain signals and each sleepstage of the determined sleep stages; controlling delivery ofneurostimulation using stimulation parameters; adjusting the stimulationparameters using the determined measure associated with the pain of thepatient for controlling the delivery of the neurostimulation during theeach sleep stage of the determined sleep stages; and delivering theneurostimulation.
 2. The method of claim 1, wherein determining thesleep stages comprises producing sleep scores using the one or moresleep signals, the sleep scores each indicative of a stage of the sleepstages and including one or more of a number, a sleep signal metric, ora number being a function of the sleep signal metric, and determiningthe measure associated with the pain of the patient using the one ormore pain signals and each stage of the determined sleep stagescomprises determining a pain score using the one or more pain signalsand the sleep score indicative of the each stage.
 3. The method of claim1, wherein sensing the one or more sleep signals from the patientcomprises sensing at least one of an accelerometer signal, a gyroscopesignal, an electrocardiogram (ECG) signal, an electroencephalogram (EEG)signal, a temperature signal of the one or more sleep signals, anelectrodermal activity (EDA) signal, a blood volume pulse (BVP) signal,or a bioelectric impedance signal.
 4. The method of claim 1, whereindelivering the neurostimulation comprises delivering theneurostimulation from a medical device implanted in the patient orexternally worn by the patient.
 5. The method of claim 4, whereinsensing the one or more sleep signals comprises sensing at least onesleep signal of the one or more sleep signals using a sensor implantedin the patient.
 6. The method of claim 4, wherein sensing the one ormore sleep signals comprises sensing at least one sleep signal of theone or more sleep signals using a sensor externally worn by the patient.7. The method of claim 4, wherein sensing the one or more sleep signalscomprises sensing at least one sleep signal of the one or more sleepsignals using a sensor communicatively coupled to the medical device viaa wireless link.
 8. The method of claim 1, wherein delivering theneurostimulation comprises delivering the neurostimulation from amedical device implanted in the patient, and sensing the one or moresleep signals comprises sensing at least one sleep signal of the one ormore sleep signals using a sensor externally worn by the patient.
 9. Themethod of claim 8, wherein sensing the one or more sleep signalscomprises sensing an electrocardiogram (ECG) signal.
 10. The method ofclaim 8, wherein sensing the one or more sleep signals comprises sensingan electroencephalogram (EEG) signal.
 11. The method of claim 1, whereinadjusting the stimulation parameters comprises optimizing thestimulation parameters for each sleep stage of the determined sleepstages.
 12. A method for delivering neurostimulation to a patient, themethod comprising: delivering a pain relief therapy including theneurostimulation to the patient; sensing one or more sleep signalsindicative of sleeping stages of the patient; determining the sleepstages of the patient using the one or more sleep signals; sensing oneor more pain signals indicative of pain of the patient; determining apain score using the one or more pain signals and each sleep stage ofthe determined sleep stages, the pain score indicative of a degree ofthe pain of the patient; determining stimulation parameters for eachsleep stage of the determined sleep stages using the determined painscore; and controlling the delivery of the neurostimulation during eachsleep stage of the determined sleep stages using stimulation parametersdetermined for that sleep stage.
 13. The method of claim 12, whereinsensing the one or more sleep signals comprises sensing anelectrocardiogram (ECG) signal.
 14. The method of claim 12, whereinsensing the one or more sleep signals comprises sensing anelectroencephalogram (EEG) signal.
 15. The method of claim 12, whereinsensing the one or more sleep signals comprises sensing at least onesleep signal of the one or more sleep signals using an external medicaldevice configured to be worn by the patient.
 16. The method of claim 15,wherein delivering the neurostimulation to the patient comprisesdelivering the neurostimulation from a neurostimulator implanted in thepatient.
 17. The method of claim 15, wherein sensing the one or moresleep signals comprises sensing at least one of an accelerometer signal,a gyroscope signal, an electrocardiogram (ECG) signal, anelectroencephalogram (EEG) signal, a temperature signal of the one ormore sleep signals, an electrodermal activity (EDA) signal, a bloodvolume pulse (BVP) signal, or a bioelectric impedance signal.
 18. Themethod of claim 15, wherein delivering the neurostimulation to thepatient comprises delivering the neurostimulation from a neurostimulatorexternally worn by the patient.
 19. The method of claim 12, whereincontrolling the delivery of the neurostimulation comprises executing aclosed-loop neurostimulation algorithm for treating chronic pain or adisorder related to the chronic pain using the determined sleep stagesas an input.
 20. The method of claim 12, wherein determining thestimulation parameters for each sleep stage of the determined sleepstages comprises optimizing the stimulation parameters for the eachstage.